1. Field
The subject matter disclosed herein relates to electronic devices, and more particularly to methods, apparatuses and articles of manufacture for use by an electronic device to track objects across two or more digital images based, at least in part, on applying a motion blur effect to a keypoint of a reference digital image.
2. Information
Various object identification and tracking techniques have been developed and continue to be developed to support computer vision. By way of example, certain techniques have been developed to provide for feature (e.g., keypoint) detection and matching of objects across different digital images, e.g., a sequence of digital images captured at different times, a video stream, etc.
The uses of computer vision appear endless. One early use of such technology included the use of computer vision for manufacturing robots to identify certain objects involved in the manufacturing process. In such instances, it may be possible to provide a significant amount of processing power and a plethora of sensors and/or cameras to assist in the processing of what may be a fairly static scene and/or at least a predictable dynamic scene.
One dramatic use of computer vision, as of recent, is its use to “augment reality” for a user of a portable electronic device. Here, for example, a portable electronic device may use computer vision techniques to identify and track certain objects within a surrounding environment, and upon recognizing its surroundings may overlay additional information on the real time video that is captured and displayed to the user. Hence, for example, a user of a mobile phone may augment certain objects, such as particularly businesses, products, services, information, etc.
Unfortunately, unlike the example of robust manufacturing robots in a fairly controlled environment, a portable electronic device may have limited processing power and find itself in an environment that may be extraordinarily dynamic at times, e.g., user walking through a busy shopping mall, an airport terminal, etc.
For these and other reasons, there is a continuing need for techniques that may be applied to computer vision, and particularly to identify and possibly track objects in dynamically active environments in an efficient manner.